Can Large Language Models Truly Act and Reason? Researchers from the University of Illinois at Urbana-Champaign Introduce LATS for Enhanced Decision-Making

LLMs have proven valuable for reasoning and decision-making tasks. They excel in breaking down complex problems into sequential steps, but their performance can be improved through methods like self-consistency and multi-step decomposition. LLMs are also effective for decision-making in various domains, though they often struggle to adapt to dynamic environments. Leveraging tree-based search methods, such […]

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